pbi_model_summary

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It discloses the tool's read-only nature implicitly through 'resumen' (summary) and explicitly lists what it reports (broken references, relationships, etc.). It also explains the 'source' parameter options (live vs pbip), adding behavioral context beyond what a summary alone would imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose. Each sentence adds value: the main summary statement, the enumerated contents, the usage recommendation, and the parameter clarification. No filler or repetition of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a model summary tool, the description is complete. It lists the key content areas (counts, table sizes, measures, calculated columns, disconnected tables, bidirectional relationships, broken references) and the source variants. Since an output schema exists, the description does not need to detail return values, and the provided information is sufficient for an agent to decide when and how to invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides only a 'source' parameter with a title and default, but no description (schema coverage 0%). The tool description compensates fully by explaining the parameter's meaning and allowed values: "`source`: 'live' (Desktop abierto) o 'pbip' (archivos TMDL)." This is directly useful for parameter selection.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: it provides a compact model summary ("Resumen compacto del modelo") with specific content items (counts, table sizes, measures per table, calculated columns, etc.). This distinguishes it from sibling tools like pbi_list_tables or pbi_analyze_model_quality by framing it as an orientation-first overview.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly recommends using this tool first to orient oneself in a model ("Es la primera tool que conviene llamar para orientarse en un modelo"). It does not enumerate alternatives or exclusions, but the 'first tool' guidance provides clear context for when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.